References considered to be relevant as background to the presently disclosed subject matter are listed below:
1. I. Azaria.; N. Goldshleger.; E. Ben-Dor.; R. Bar-Hamburger “Detection of Cannabis Plants by Hyper-Spectral Remote Sensing Means”. Tel Aviv University Publication, Horizons in Geography, 2011, Vol. 77, pp. 59-73.
2. K. D Shepherd.; M. G. Walsh (2007) “Infrared spectroscopy enabling an evidence-based diagnostic surveillance approach to agricultural and environmental management in developing countries”. J. Near Infrared Spectrosc. 15: 1-19.
3. Hans Grahn; Paul Geladi (2007). “Techniques and Applications of Hyperspectral Image Analysis”. John Wiley & Sons.
4. Higgins, Kevin (2013). “Five New Technologies for Inspection”. Food Processing
5. Wernick, Yang.; Brankov.; Yourganov Strother (2010) “Machine Learning in Medical Imaging”. IEEE Signal Processing Magazine 27 (4): 25-38.
6. C. M. Bishop (2006). “Pattern Recognition and Machine Learning”. Springer.
7. United Nations New York, Laboratory and Scientific Section UN Office on Drugs and Crime Vienna (2009) “Recommended Methods for the Identification and Analysis of Cannabis and Cannabis Products” Manual for use by National Drug Analysis Laboratories.
8. Analytical Monograph Cannabis Flos (flowers/granulated) OMC/Farmalyse BV Version 7.1/Nov. 28, 2014
9. Swift W, Wong A, Li K M, Arnold J C, McGregor L S, 2013, Analysis of cannabis seizures in NSW, Australia, cannabis potency and cannabinoid profile. PLOS ONE 8: e70052.
10. DeBacker B, Debrus B, Lebrun P, Theunis L, Dubios N, Decock L, Verstraete A, Hubert P, Charlier C, 2009, Innovative development and validation of an HPLC/DAD method for the qualitative and quantitative determination of major cannabinoids in cannabis plants materials. J Chromatogr B, 877, 4115-24
11. American Herbal Pharmacopoeia, cannabis inflorescence, standards of identity, Analysis and quality control, 2013
Acknowledgement of the above references herein is not to be inferred as meaning that these are in any way relevant to the patentability of the presently disclosed subject matter.